Determining a Deployment Schedule for Operations Performed on Devices Using Device Dependencies and Redundancies

2. The apparatus of claim 1 wherein the plurality of devices comprise Internet of Things devices.

4. The apparatus of claim 1 wherein the operation comprises updating at least one application on the selected device.

6. The apparatus of claim 4 wherein the operation is performed using an in-place update mechanism responsive to a negative determination that the selected device corresponds to the additional device.

7. The apparatus of claim 1 wherein the model of the plurality of devices comprises a directed weighted graph with nodes representing the plurality of devices and edges between the nodes representing call relationships between the plurality of devices.

8. The apparatus of claim 7 wherein a given edge weight associated with a given edge between a first node and a second node in the directed weighted graph is based at least in part on a number of requests between the first node and the second node and an amount of data exchanged between the first node and the second node.

9. The apparatus of claim 1 wherein building the device dependency chain for the plurality of devices comprises computing an overall dependency score for each of the plurality of devices, the overall dependency score for a given device comprising a sum of pairwise dependency scores characterizing activity between the given device and each of at least a subset of other ones of the plurality of devices that have call relationships with the given device.

10. The apparatus of claim 1 wherein the given time period comprises a day, and the one or more time slots comprise hours in the day.

11. The apparatus of claim 1 wherein predicting the workload for each of the plurality of devices in the one or more time slots of the given time period comprises utilizing a machine learning regression analysis.

12. The apparatus of claim 11 wherein the machine learning regression analysis comprises a multivariate linear regression analysis.

13. The apparatus of claim 12 wherein the multivariate linear regression analysis is based at least in part on two or more of processor utilization of the plurality of devices, memory utilization of the plurality of devices, availability of the plurality of devices, response time of the plurality of devices, and disk utilization of the plurality of devices.

15. The apparatus of claim 1 wherein the deployment schedule specifies a sequence in which the operation is to be performed on the plurality of devices.